SDoH-Aware Narrative Anchoring Bias in Medical LLMs for Trustworthy Clinical Decision Support
arXiv:2608.22802v1 Announce Type: cross Abstract: Medical large language models are often judged by how many clinical questions they answer correctly.…
arXiv:2608.22802v1 Announce Type: cross Abstract: Medical large language models are often judged by how many clinical questions they answer correctly.…
arXiv:2608.22617v1 Announce Type: cross Abstract: Assembly and disassembly processes rely on expert knowledge that is difficult to document, reuse, and…
arXiv:2608.00013v2 Announce Type: replace-cross Abstract: Choosing the right large language model (LLM) backbone is the most consequential decision when building…
arXiv:2608.21106v2 Announce Type: replace-cross Abstract: The Atom Learning Model (ALM) tokenises a school curriculum. Two secondary mathematics textbooks were read…
arXiv:2608.20169v2 Announce Type: replace-cross Abstract: We present a novel approach to efficient LLM harness optimization through adaptive validation task selection.…
arXiv:2606.03770v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become integral to modern applications, yet their deployment remains challenging.…
arXiv:2608.01947v2 Announce Type: replace-cross Abstract: The ability to robustly maintain and update continuous variables is a hallmark of working memory.…
arXiv:2608.22800v1 Announce Type: cross Abstract: Ensuring reliability in uncertain environments remains difficult for long-horizon robotic manipulation. End-to-end VLA models are…
arXiv:2608.19885v2 Announce Type: replace-cross Abstract: After the inputs X are known, how much additional information does the label Y carry…